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Data Analyst with 1+ years in statistical analysis, data cleaning & QC automation
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Assessing your cultural and operational fit
Data Analyst with 1.5+ years of experience in statistical analysis, data cleaning, QC automation, and research reporting. Proficient in Python, SQL, Base SAS and R—building efficient analytical pipelines that deliver key insights from complex datasets. Published in The Lancet Global Health; proven at producing audit-ready data products for international research teams with strong attention to detail.
Savitribai Phule Pune University
M.Sc. · Statistics
August 1, 2021 – June 30, 2023
Modern College Shivajinagar
B.Sc. · Statistics
August 1, 2018 – June 30, 2021
Dr. D.Y. Patil Hospital, Medical College & Research Centre
Statistician Data Analyst
August 1, 2024 – December 1, 2025
Pune, Maharashtra, India
Optical Character Recognition - Devanagari Script
June 18, 2026 – Present
Benchmarked k-NN (90%) vs CNN (98%) for handwritten character recognition; documented model performance tradeoffs and accuracy metrics in a structured analytical report.
Maternal Health Risk Prediction
June 18, 2026 – Present
Built a Random Forest predictive model achieving 85.15% accuracy, outperforming SVM and Logistic Regression benchmarks; identified key maternal risk factors and visualised distributions using ggplot2 for stakeholder reporting.
International Poster Presentation
STIAS Institute
January 1, 2025 – Present
Paper Accepted
The Lancet Global Health
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic background in Statistics, coupled with practical experience in clinical research, indicates a strong analytical mindset and a commitment to data integrity. The project diversity (health risk prediction, OCR) and experience in a collaborative research setting (Johns Hopkins co-investigators) suggest adaptability and a collaborative spirit. The publication in 'The Lancet Global Health' and international presentation highlight a drive for impact and recognition, aligning well with a culture that values rigorous, high-quality work.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills including attention to detail, problem-solving, stakeholder communication, cross-functional collaboration, and competing priorities management. These are critical for operational fit in a data-driven role, especially given the experience in a research environment with international deadlines and publication requirements.